More from Daniel Marino
I’m a bit late to this, but back in summer 2024 I participated in the OST Composing Jam. The goal of this jam is to compose an original soundtrack (minimum of 3 minutes) of any style for an imaginary game. While I’ve composed a lot of video game music, I’ve never created an entire soundtrack around a single concept. Self Avoiding Walk by Daniel Marino To be honest, I wasn’t entirely sure where to start. I was torn between trying to come up with a story for a game to inspire the music, and just messing around with some synths and noodling on the keyboard. I did a little bit of both, but nothing really materialized. Synth + Metal ≈ Synthmetal Feeling a bit paralyzed, I fired up the ’ole RMG sequencer for inspiration. I saved a handful of randomized melodies and experimented with them in Reaper. After a day or two I landed on something I liked which was about the first 30 seconds or so of the second track: "Defrag." I love metal bands like Tesseract, Periphery, The Algorithm, Car Bomb, and Meshuggah. I tried experimenting with incorporating syncopated guttural guitar sounds with the synths. After several more days I finished "Defrag"—which also included "Kernel Panic" before splitting that into its own track. I didn’t have a clue what to do next, nor did I have a concept. Composing the rest of the music was a bit of a blur because I bounced around from song to song—iterating on the leitmotif over and over with different synths, envelopes, time signatures, rhythmic displacement, pitch shifting, and tweaking underlying chord structures. Production The guitars were recorded using DI with my Fender Squire and Behringer Interface. I’m primarily using the ML Sound Labs Amped Roots Free amp sim because the metal presets are fantastic and rarely need much fuss to get it sounding good. I also used Blue Cat Audio free amp sim for clean guitars. All the other instruments were MIDI tracks either programmed via piano roll or recorded with my Arturia MiniLab MKII. I used a variety of synth effects from my library of VSTs. I recorded this music before acquiring my Fender Squire Bass guitar, so bass was also programmed. Theme and Story At some point I had five songs that all sounded like they could be from the same game. The theme for this particular jam was "Inside my world." I had to figure out how I could write a story that corresponded with the theme and could align with the songs. I somehow landed on the idea of the main actor realizing his addiction to AI, embarking on a journey to "unplug." The music reflects his path to recovery, capturing the emotional and psychological evolution as he seeks to overcome his dependency. After figuring this out, I thought it would be cool to name all the songs using computer terms that could be metaphors for the different stages of recovery. Track listing Worm – In this dark and haunting opening track, the actor grapples with his addiction to AI, realizing he can no longer think independently. Defrag – This energetic track captures the physical and emotional struggles of the early stages of recovery. Kernel Panic – Menacing and eerie, this track portrays the actor’s anxiety and panic attacks as he teeters on the brink during the initial phases of recovery. Dæmons – With initial healing achieved, the real challenge begins. The ominous and chaotic melodies reflect the emotional turbulence the character endures. Time to Live – The actor, having come to terms with himself, experiences emotional growth. The heroic climax symbolizes the realization that recovery is a lifelong journey. Album art At the time I was messing around with Self-avoiding walks in generative artwork explorations. I felt like the whole concept of avoiding the self within the context of addiction and recovery metaphorically worked. So I tweaked some algorithms and generated the self-avoiding walk using JavaScript and the P5.js library. I then layered the self-avoiding walk over a photo I found visually interesting on Unsplash using a CSS blend mode. Jam results I placed around the top 50% out of over 600 entries. I would have liked to have placed higher, but despite my ranking, I thoroughly enjoyed composing the music! I’m very happy with the music, its production quality, and I also learned a lot. I would certainly participate in this style of composition jam again!
I’ve always been fascinated to see what other apps or workflows others are using in their day-to-day lives. Every now and then I learn about a new app or some cool trick I didn’t previously know. I doubt anyone seriously cares about what I’m using, but figured I’d list them out anyway—if for no other reason than to keep a historical record at this point in time. Applications Alfred — I have a lifelong license, and I like it. No point in fixing something that isn’t broken. I primarily use it for app switching, but also use it for math, and to search for gifs. Aseprite — Sometimes I do pixel art! Even if the UI is clunky, and some keyboard shortcuts aren’t always convenient, there are some unique features that help facilitate creating pixel art. Audacity — I rarely use it, but sometimes it’s easier to make some quick audio edits with Audacity than to use a full blown DAW. Bear — This is the note-taking, task-tacking app I’ve landed on. The UI is beautiful and it feels snappy. It syncs, so I can use it on my iPhone too. Chrome — I used Arc for the better part of 2024, but after they announced they were done working on it to focus on a new AI-powered browser, I peaced out. There are a couple of features I really missed, but was able to find some extensions to fill those gaps: Copy Current Tab URL, Meetings Page Auto Closer for Zoom, Open Figma app, and JSON Formatter. Figma — I use it because it’s what we use at work. I’m happy enough with Figma. iTerm2 — Has a few features that I like that makes me chose this over Mac’s native Terminal app. Pixelmator Pro — I haven’t paid the Adobe tax for a long time, and it feels good. I started using Pixelmator because at the time it was the best alternative available. I’m comfortable with Pixelmator at this point. I don’t really use image editors often these days, so I probably won’t switch anytime soon. Reaper — My DAW of choice when composing music. It’s very customizable, easyish enough to learn, and the price is right. It also has a die hard community, so I’m always able to find help when I need it. VS Code — I’ve tried a lot of code editors. I prefer Sublime’s UI over VS Code, but VS Code does a lot of things more easily than Sublime does, so I put up with the UI. YouTube Music — I still miss Rdio. YouTube Music works well enough I guess. Paying for YouTube Music has the benefit of not seeing ads on YouTube. Command-line Tools These aren’t apps per se, but these are some tools that I use to help manage packages or that I use regularly when developing. Deno Eleventy Homebrew pure statikk Vite Volta yt-dlp Equipment I have one computer and I use it for everything, and I’m okay with that. It’s more than powerful enough for work, composing music, making games, and occasionaly playing games. Although I have a dedicated home office, lately I tend to work more on the go, often with just my laptop—whether that’s at a cafe, a coworking space, or even just moving around the house. 2021 M1 MacBook Pro AKG K240 Studio Headphones Arturia MiniLab MKII Controller Behringer UMC202HD USB Audio Interface Fender Squire Strat Guitar Fender Squire Bass Guitar Shure SM57 Virtual Instruments This is quite specific for composing music, so if that does’t interest you, feel free to stop reading here. This list is not exhaustive as I’m regularly trying out new VSTs. These are some staples that I use: 🎹 Arturia Analog Lab V (Intro) — My Arturia controller came with this software. It has over 500 presets and I love exploring the variety of sounds. 🎸 Bass Grinder (Free) — I recently came across this VST, and it has a great crunchy overdrive sound for bass guitar. 🥁 Manda Audio Power Drum Kit — Even though you can use this for free, I paid the $9 because it is fantastic. The drums sound real and are great for all styles of music. 🎸 ML Amped Roots (Free) — What I like about this is that I get great metal guitar out of the bost without having to add pedals or chaining other effects. 🥁 ML Drums (Free) — I just started experimenting with this, and the drum tones are amazing. The free set up is pretty limited, but I like how I can add on to the base drum kit to meet my needs rather than having having to buy one big extensive drum VST. 🎹 Spitfire LABS — More variety of eclectic sounds. I also use several built-in VSTs made by Reaper for delay, EQ, reverb, pitch-shifting, and other effects. Reaper’s VSTs are insanely powerful enough for my needs and are much less CPU intensive.
Over the past couple of years I’ve gotten into journaling. Recently I’ve been using a method where you’re given a single inspirational word as a prompt, and go from there. Unfortunately, the process of finding, saving, and accessing inspirational words was a bit of a chore: Google a list of “366 inspirational words”. Get taken to a blog bloated with ads and useless content all in an effort to generate SEO cred. Copy/paste the words into Notion. Fix how the words get formatted becasue Notion is weird, and I have OCD about formatting text. While this gets the job done, I felt like there was room to make this a more pleasant experience. All I really wanted was a small website that serves a single inspirational word on a daily basis without cruft or ads. This would allow me to get the content I want without having to scroll through a long list. I also don't want to manage or store the list of words. Once I've curated a list of words, I want to be done with it. Creating a microsite I love a good microsite, and so I decided to create one that takes all the chore out of obtaining a daily inspirational word. The website is built with all vanilla tech, and doesn’t use any frameworks! It’s nice and lean, and it’s footprint is only 6.5kb. Inspirational words While I’m not a huge fan of AI, I did leverage ChatGPT on obtaining 366 inspirational words. The benefit to ChatGPT was being able to get it to return the words as an array—cutting down on the tedium of having to convert the words I already had into an array. The words are stored in it’s own JSON file, and I use an async/await function to pull in the words, and then process the data upon return. Worth the effort I find these little projects fun and exciting because the scope is super tight, and makes for a great opportunity to learn new things. It’s definitely an overengineered solution to my problem, but it is a much more pleasant experience. And perhaps it will serve other people as well.
Over the past couple of years I’ve gotten into journaling. Recently I’ve been using a method where you’re given a single inspirational word as a prompt, and go from there. Unfortunately, the process of finding, saving, and accessing inspirational words was a bit of a chore: 1. Google a list of “366 inspirational words”. 2. Get taken to a blog bloated with ads and useless content all in an effort to generate SEO cred. 3. Copy/paste the words into Notion. 4. Fix how the words get formatted becasue Notion is weird, and I have OCD about formatting text. While this gets the job done, I felt like there was room to make this a more pleasant experience. All I really wanted was a small website that serves a single inspirational word on a daily basis without cruft or ads. This would allow me to get the content I want without having to scroll through a long list. I also don't want to manage or store the list of words. Once I've curated a list of words, I want to be done with it. ## Creating a microsite I love a good microsite, and so I decided to create one that takes all the chore out of obtaining a [daily inspirational word](https://starzonmyarmz.github.io/daily-inspirational-word/).  The website is built with all vanilla tech, and doesn’t use any frameworks! It’s nice and lean, and it’s footprint is only 6.5kb. ### Inspirational words While I’m not a huge fan of AI, I did leverage ChatGPT on obtaining 366 inspirational words. The benefit to ChatGPT was being able to get it to return the words as an array—cutting down on the tedium of having to convert the words I already had into an array. The words are stored in it’s own JSON file, and I use an async/await function to pull in the words, and then process the data upon return. ## Worth the effort I find these little projects fun and exciting because the scope is super tight, and makes for a great opportunity to learn new things. It’s definitely an overengineered solution to my problem, but it is a much more pleasant experience. And perhaps it will serve other people as well.
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Have I told you how much I've come to dislike the 90s? The depressive music, the ironic distance to everything, the deconstructive narratives, the moral relativism, and the total cultural takeover of postmodern ideology. Oh, I did that just last week? Well, allow me another go. But rather than railing against the 90s, let me tell you about the 80s. They were amazing. America was firing on all cylinders, Reagan had brought the morning back, and the Soviet Union provided a clear black-and-white adversarial image. But it was the popular culture of the era that still fills me with hiraeth. It was the time of earnest storytelling. When Rocky could just train real hard to avenge the death of his friend by punching Dolph Lundgreen for 10 minutes straight in a montage of blood, sweat, and tears. After which even the Russians couldn't help themselves but cheer for him. Not a shred of irony. Just pure "if you work real hard, you can do the right thing" energy. Or what about Weird Science from 1985? Two nerds bring Barbie to life, and she teaches them to talk to real girls. It was goofy, it was kitsch, but it was also earnest and honest. Nerdy teenage boys have a hard time talking to girls! But they can learn how, and if they do, it'll all work out. That movie was actually the earliest memory I have of wanting to move to America. I don't remember exactly when I saw it, but I remember at the end thinking, "I have to go there." Such was the magnetic power of that American 80s earnest optimism! Or what about the music? Do you have any idea what the 1986 music video for Sabrina's BOYS could do for a young Danish boy who'd only just discovered the appeal of girls? Wonders, is what. Wonders. And again, it depicted this goofy but earnest energy. Boys and girls like each other! They have fun with the chase. The genders are not doomed to opposing trenches on the Eastern Front for all eternity. So back to today. It feels like we're finally emerging from this constant 90s Seattle drizzle to sunny 80s LA vibes in America. The constant pessimism, the cancellation militias, and the walking-on-eggshells atmosphere have given way to something far brighter, bolder, and, yes, better. An optimism, a levity, a confidence. First, America has Sweeney fever. The Sydney Sweeney Has Great Jeans campaign has been dominating the discourse for weeks, but rather than back down with a groveling apology, American Eagle has doubled down with a statement and now the Las Vegas sphere! And Sweeney herself has also kept her foot on the gas. Now there's a new Baskin-Robbins campaign that's equal parts Weird Science (two nerds!) and "Boys Boys Boys" music video. No self-referential winks to how this might achksually be ProBLeMAtIC. Just a confident IT GIRL grabbing the attention of a nation. The male role model too has been going through a rehabilitation lately. I absolutely loved F1: The Movie. It's classic Jerry Bruckheimer Top Gun pathos: Real men doing dangerous stuff for the chase, the glory, and the next generation with a love story that involves a competent yet feminine female partner. Again, it's an entirely sincere story with great morals. The generational gap is real, but we can learn from each other. Young hotshots have speed but lack experience. Old-timers can be grumpy but their wisdom was hard-won. Even the diversity in that movie fails to feel forced! It's a woman leading the engineering in a male-dominated world, and she can't quite hack it at first. Her designs are too by-the-book. But then Brad Pitt sells the gamble of a dirty-air fighter design, she steps up her game, and wins the crown by her wits and talent. Tell me that isn't a wholesome story! David Foster Wallace nailed this all in his critique of postmodernism. He called out the irony, cynicism, and irreverence that had fully permeated the culture from the 90s forward. And frankly, he was bored with it! It's an amazing interview to watch today. Wallace had the diagnosis nailed back in 1997. But it's taken us until these mid-2020s to fully embrace its conclusions. We need earnest values and virtues. We need sincere stories that are not afraid of grand narratives. That don't constantly have to deconstruct "but what is good really?", and dare embrace a solid defense of "some ways of being really are better." We also need to have fun! We need to throw away these shit-tinted glasses that see everything in the world as a problematic example of some injustice or oppression. We a bit of gratitude for technology and progress! That's what the Sweeney campaign is doing. That's what Brad Pitt is racing for in F1: The Movie. That's what I'm here for! Because as much as I love the croissants of the Old World, I find myself craving that uniquely American brand of optimism, enthusiasm, and determination more whenever I've been back in Europe for too long. Give me some Weird Science! Give me some Sabrina at the pool! Give me some American 80s vibes!
I was listening to a podcast interview with the Jackson Browne (American singer/songwriter, political activist, and inductee into the Rock and Roll Hall of Fame) and the interviewer asks him how he approaches writing songs with social commentaries and critiques — something along the lines of: “How do you get from the New York Times headline on a social subject to the emotional heart of a song that matters to each individual?” Browne discusses how if you’re too subtle, people won’t know what you’re talking about. And if you’re too direct, you run the risk of making people feel like they’re being scolded. Here’s what he says about his songwriting: I want this to sound like you and I were drinking in a bar and we’re just talking about what’s going on in the world. Not as if you’re at some elevated place and lecturing people about something they should know about but don’t but [you think] they should care. You have to get to people where [they are, where] they do care and where they do know. I think that’s a great insight for anyone looking to have a connecting, effective voice. I know for me, it’s really easily to slide into a lecturing voice — you “should” do this and you “shouldn’t” do that. But I like Browne’s framing of trying to have an informal, conversational tone that meets people where they are. Like you’re discussing an issue in the bar, rather than listening to a sermon. Chris Coyier is the canonical example of this that comes to mind. I still think of this post from CSS Tricks where Chris talks about how to have submit buttons that go to different URLs: When you submit that form, it’s going to go to the URL /submit. Say you need another submit button that submits to a different URL. It doesn’t matter why. There is always a reason for things. The web is a big place and all that. He doesn’t conjure up some universally-applicable, justified rationale for why he’s sharing this method. Nor is there any pontificating on why this is “good” or “bad”. Instead, like most of Chris’ stuff, I read it as a humble acknowledgement of the practicalities at hand — “Hey, the world is a big place. People have to do crafty things to make their stuff work. And if you’re in that situation, here’s something that might help what ails ya.” I want to work on developing that kind of a voice because I love reading voices like that. Email · Mastodon · Bluesky
Previously, I wrote some sketchy ideas for what I call a p-fast trie, which is basically a wide fan-out variant of an x-fast trie. It allows you to find the longest matching prefix or nearest predecessor or successor of a query string in a set of names in O(log k) time, where k is the key length. My initial sketch was more complicated and greedy for space than necessary, so here’s a simplified revision. (“p” now stands for prefix.) layout A p-fast trie stores a lexicographically ordered set of names. A name is a sequence of characters from some small-ish character set. For example, DNS names can be represented as a set of about 50 letters, digits, punctuation and escape characters, usually one per byte of name. Names that are arbitrary bit strings can be split into chunks of 6 bits to make a set of 64 characters. Every unique prefix of every name is added to a hash table. An entry in the hash table contains: A shared reference to the closest name lexicographically greater than or equal to the prefix. Multiple hash table entries will refer to the same name. A reference to a name might instead be a reference to a leaf object containing the name. The length of the prefix. To save space, each prefix is not stored separately, but implied by the combination of the closest name and prefix length. A bitmap with one bit per possible character, corresponding to the next character after this prefix. For every other prefix that matches this prefix and is one character longer than this prefix, a bit is set in the bitmap corresponding to the last character of the longer prefix. search The basic algorithm is a longest-prefix match. Look up the query string in the hash table. If there’s a match, great, done. Otherwise proceed by binary chop on the length of the query string. If the prefix isn’t in the hash table, reduce the prefix length and search again. (If the empty prefix isn’t in the hash table then there are no names to find.) If the prefix is in the hash table, check the next character of the query string in the bitmap. If its bit is set, increase the prefix length and search again. Otherwise, this prefix is the answer. predecessor Instead of putting leaf objects in a linked list, we can use a more complicated search algorithm to find names lexicographically closest to the query string. It’s tricky because a longest-prefix match can land in the wrong branch of the implicit trie. Here’s an outline of a predecessor search; successor requires more thought. During the binary chop, when we find a prefix in the hash table, compare the complete query string against the complete name that the hash table entry refers to (the closest name greater than or equal to the common prefix). If the name is greater than the query string we’re in the wrong branch of the trie, so reduce the length of the prefix and search again. Otherwise search the set bits in the bitmap for one corresponding to the greatest character less than the query string’s next character; if there is one remember it and the prefix length. This will be the top of the sub-trie containing the predecessor, unless we find a longer match. If the next character’s bit is set in the bitmap, continue searching with a longer prefix, else stop. When the binary chop has finished, we need to walk down the predecessor sub-trie to find its greatest leaf. This must be done one character at a time – there’s no shortcut. thoughts In my previous note I wondered how the number of search steps in a p-fast trie compares to a qp-trie. I have some old numbers measuring the average depth of binary, 4-bit, 5-bit, 6-bit and 4-bit, 5-bit, dns qp-trie variants. A DNS-trie varies between 7 and 15 deep on average, depending on the data set. The number of steps for a search matches the depth for exact-match lookups, and is up to twice the depth for predecessor searches. A p-fast trie is at most 9 hash table probes for DNS names, and unlikely to be more than 7. I didn’t record the average length of names in my benchmark data sets, but I guess they would be 8–32 characters, meaning 3–5 probes. Which is far fewer than a qp-trie, though I suspect a hash table probe takes more time than chasing a qp-trie pointer. (But this kind of guesstimate is notoriously likely to be wrong!) However, a predecessor search might need 30 probes to walk down the p-fast trie, which I think suggests a linked list of leaf objects is a better option.
New Logic for Programmers Release! v0.11 is now available! This is over 20% longer than v0.10, with a new chapter on code proofs, three chapter overhauls, and more! Full release notes here. Software books I wish I could read I'm writing Logic for Programmers because it's a book I wanted to have ten years ago. I had to learn everything in it the hard way, which is why I'm ensuring that everybody else can learn it the easy way. Books occupy a sort of weird niche in software. We're great at sharing information via blogs and git repos and entire websites. These have many benefits over books: they're free, they're easily accessible, they can be updated quickly, they can even be interactive. But no blog post has influenced me as profoundly as Data and Reality or Making Software. There is no blog or talk about debugging as good as the Debugging book. It might not be anything deeper than "people spend more time per word on writing books than blog posts". I dunno. So here are some other books I wish I could read. I don't think any of them exist yet but it's a big world out there. Also while they're probably best as books, a website or a series of blog posts would be ok too. Everything about Configurations The whole topic of how we configure software, whether by CLI flags, environmental vars, or JSON/YAML/XML/Dhall files. What causes the configuration complexity clock? How do we distinguish between basic, advanced, and developer-only configuration options? When should we disallow configuration? How do we test all possible configurations for correctness? Why do so many widespread outages trace back to misconfiguration, and how do we prevent them? I also want the same for plugin systems. Manifests, permissions, common APIs and architectures, etc. Configuration management is more universal, though, since everybody either uses software with configuration or has made software with configuration. The Big Book of Complicated Data Schemas I guess this would kind of be like Schema.org, except with a lot more on the "why" and not the what. Why is important for the Volcano model to have a "smokingAllowed" field?1 I'd see this less as "here's your guide to putting Volcanos in your database" and more "here's recurring motifs in modeling interesting domains", to help a person see sources of complexity in their own domain. Does something crop up if the references can form a cycle? If a relationship needs to be strictly temporary, or a reference can change type? Bonus: path dependence in data models, where an additional requirement leads to a vastly different ideal data model that a company couldn't do because they made the old model. (This has got to exist, right? Business modeling is a big enough domain that this must exist. Maybe The Essence of Software touches on this? Man I feel bad I haven't read that yet.) Computer Science for Software Engineers Yes, I checked, this book does not exist (though maybe this is the same thing). I don't have any formal software education; everything I know was either self-taught or learned on the job. But it's way easier to learn software engineering that way than computer science. And I bet there's a lot of other engineers in the same boat. This book wouldn't have to be comprehensive or instructive: just enough about each topic to understand why it's an area of study and appreciate how research in it eventually finds its way into practice. MISU Patterns MISU, or "Make Illegal States Unrepresentable", is the idea of designing system invariants in the structure of your data. For example, if a Contact needs at least one of email or phone to be non-null, make it a sum type over EmailContact, PhoneContact, EmailPhoneContact (from this post). MISU is great. Most MISU in the wild look very different than that, though, because the concept of MISU is so broad there's lots of different ways to achieve it. And that means there are "patterns": smart constructors, product types, properly using sets, newtypes to some degree, etc. Some of them are specific to typed FP, while others can be used in even untyped languages. Someone oughta make a pattern book. My one request would be to not give them cutesy names. Do something like the Aarne–Thompson–Uther Index, where items are given names like "Recognition by manner of throwing cakes of different weights into faces of old uncles". Names can come later. The Tools of '25 Not something I'd read, but something to recommend to junior engineers. Starting out it's easy to think the only bit that matters is the language or framework and not realize the enormous amount of surrounding tooling you'll have to learn. This book would cover the basics of tools that enough developers will probably use at some point: git, VSCode, very basic Unix and bash, curl. Maybe the general concepts of tools that appear in every ecosystem, like package managers, build tools, task runners. That might be easier if we specialize this to one particular domain, like webdev or data science. Ideally the book would only have to be updated every five years or so. No LLM stuff because I don't expect the tooling will be stable through 2026, to say nothing of 2030. A History of Obsolete Optimizations Probably better as a really long blog series. Each chapter would be broken up into two parts: A deep dive into a brilliant, elegant, insightful historical optimization designed to work within the constraints of that era's computing technology What we started doing instead, once we had more compute/network/storage available. c.f. A Spellchecker Used to Be a Major Feat of Software Engineering. Bonus topics would be brilliance obsoleted by standardization (like what people did before git and json were universal), optimizations we do today that may not stand the test of time, and optimizations from the past that did. Sphinx Internals I need this. I've spent so much goddamn time digging around in Sphinx and docutils source code I'm gonna throw up. Systems Distributed Talk Today! Online premier's at noon central / 5 PM UTC, here! I'll be hanging out to answer questions and be awkward. You ever watch a recording of your own talk? It's real uncomfortable! In this case because it's a field on one of Volcano's supertypes. I guess schemas gotta follow LSP too ↩